RoBERTa_conll_epoch_9
This model is a fine-tuned version of distilroberta-base on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0841
- Precision: 0.9447
- Recall: 0.9574
- F1: 0.9510
- Accuracy: 0.9884
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0779 | 1.0 | 1756 | 0.0640 | 0.9142 | 0.9359 | 0.9249 | 0.9836 |
0.0448 | 2.0 | 3512 | 0.0867 | 0.9220 | 0.9364 | 0.9291 | 0.9836 |
0.03 | 3.0 | 5268 | 0.0580 | 0.9263 | 0.9482 | 0.9371 | 0.9865 |
0.018 | 4.0 | 7024 | 0.0760 | 0.9330 | 0.9490 | 0.9409 | 0.9864 |
0.0108 | 5.0 | 8780 | 0.0733 | 0.9363 | 0.9544 | 0.9452 | 0.9873 |
0.0096 | 6.0 | 10536 | 0.0773 | 0.9413 | 0.9534 | 0.9473 | 0.9879 |
0.0039 | 7.0 | 12292 | 0.0755 | 0.9442 | 0.9561 | 0.9501 | 0.9885 |
0.0024 | 8.0 | 14048 | 0.0834 | 0.9425 | 0.9567 | 0.9496 | 0.9884 |
0.0006 | 9.0 | 15804 | 0.0841 | 0.9447 | 0.9574 | 0.9510 | 0.9884 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Downloads last month
- 8
Model tree for ICT2214Team7/RoBERTa_conll_epoch_9
Base model
distilbert/distilroberta-baseDataset used to train ICT2214Team7/RoBERTa_conll_epoch_9
Evaluation results
- Precision on conll2003validation set self-reported0.945
- Recall on conll2003validation set self-reported0.957
- F1 on conll2003validation set self-reported0.951
- Accuracy on conll2003validation set self-reported0.988